Agentic data science with the Data Agent Kit
cloud.google.com·6h ago
AI Research
arXiv CS.AI·Aug 19·5 min read
Runtime Governance for Agentic AI: Action-Boundary Control with Trusted Provenance and Fail-Closed Execution
TL;DR
Aegis is a runtime governance system for agentic AI that evaluates action proposals through a trusted decision layer, preventing risky operational side effects. In tests, Aegis achieved zero risky completions across 2,100 governed actions, demonstrating effective action-boundary control.
✦ Why It Matters
Implement Aegis to enhance safety in your AI systems by controlling action proposals and preventing harmful side effects.
Key Takeaways
- Integrate Aegis for safer AI tool actions.
- Utilize server-side provenance for accountability.
- Adopt fail-closed mechanisms to handle uncertainties.
- Implement quorum-based authorization for decision-making.
How It Works
Aegis operates by treating AI-generated outputs as proposals for actions. These proposals are evaluated against active policies and resolved through a trusted decision layer.
If uncertainty arises, Aegis fails closed, meaning it will not execute potentially harmful actions. The system also employs a Senate-style settlement process, requiring a quorum for authorization, ensuring that no single entity can unilaterally approve actions.